Universidad Complutense de Madrid
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Fuzzy sets in remote sensing classification.

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Gomez, Daniel y Montero, Javier (2008) Fuzzy sets in remote sensing classification. Soft Computing, 12 . pp. 243-249. ISSN 1432-7643

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Supervised classification in remote sensing is a very complex problem and involves steps of different nature, including a serious data preprocessing. The final objective can be stated in terms of a classification of isolated pixels between classes, which can be either previously known or not (for example, different land uses), but with no particular shape nither well defined borders. Hence, a fuzzy approach seems natural in order to capture the structure of the image. In this paper we stress that some useful tools for a fuzzy classification can be derived from fuzzy coloring procedures, to be extended in a second stage to the complete non visible spectrum. In fact, the image is considered here as a fuzzy graph defined on the set of pixels, taking advantage of fuzzy numbers in order to summarize information. A fuzzy model is then presented, to be considered as a decision making aid tool. In this way we generalize the classical definition of fuzzy partition due to Ruspini, allowing in addition a first evaluation of the quality of the classification in this way obtained, in terms of three basic indexes (measuring covering, relevance and overlapping of our family of classes).


Tipo de documento:Artículo
Palabras clave:Fuzzy classification systems; Remote sensing; Fuzzy graph
Materias:Ciencias > Matemáticas > Estadística matemática
Código ID:16297
Depositado:10 Sep 2012 09:45
Última Modificación:19 Abr 2016 17:03

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